See here
As I do more WebGPU I find I need more and more helpers to make things less tedious. These are the result. I expect I'll add more over time.
Example:
import {
makeShaderDataDefinitions,
makeStructuredView,
} from 'webgpu-utils';
const code = `
struct MyUniforms {
color: vec4f,
brightness: f32,
kernel: array<f32, 9>,
projectionMatrix: mat4x4f,
};
@group(0) @binding(0) var<uniform> myUniforms: MyUniforms;
`;
const defs = makeShaderDataDefinitions(code);
const myUniformValues = makeStructuredView(defs.uniforms.myUniforms);
// create the correct sized buffer
const uniformBuffer = device.createBuffer({
size: myUniformValues.arrayBuffer.byteLength,
usage: GPUBufferUsage.UNIFORM | GPUBufferUsage.COPY_DST,
});
// Set some values via set
myUniformValues.set({
color: [1, 0, 1, 1],
brightness: 0.8,
kernel: [
1, 0, -1,
2, 0, -2,
1, 0, -1,
],
});
// Set a value by passing it to a math library
mat4.perspective(
degToRad(45),
canvas.clientWidth / canvas.clientHeight,
0.1,
20,
myUniformValues.views.projectionMatrix);
// Upload the data to the GPU
device.queue.writeBuffer(uniformBuffer, 0, myUniformValues.arrayBuffer);
See makeStructuredView for details.
import { createTextureFromImage } from 'webgpu-utils';
const texture = await createTextureFromImage(device, 'https://someimage.url', {
mips: true,
flipY: true,
});
import { createTextureFromSource } from 'webgpu-utils';
const texture = createTextureFromSource(device, someCanvasVideoImageBitmap, {
mips: true,
flipY: true,
});
import { createTextureFromImage } from 'webgpu-utils';
const texture = await createTextureFromImages(device, [
'images/yokohama/posx.jpg',
'images/yokohama/negx.jpg',
'images/yokohama/posy.jpg',
'images/yokohama/negy.jpg',
'images/yokohama/posz.jpg',
'images/yokohama/negz.jpg',
], {
mips: true,
});
import { createTextureFromSource } from 'webgpu-utils';
const r = [255, 0, 0, 255];
const g = [ 0, 255, 0, 255];
const b = [ 0, 0, 255, 255];
const y = [255, 255, 0, 255];
// if no width or height is passed, then assumes data is rgba8unorm
// if sqrt(numPixels) is in then makes a square. Otherwise Nx1
const data2x2 = [ r, g, b, y ].flat();
const texture2x2 = createTextureFromSource(device, data2x2, {
mips: true,
});
const data4x1 = {
data: [ r, g, b, y ].flat();
width: 4,
};
const texture4x1 = createTextureFromSource(device, data2x2, {
mips: true,
});
const singlePixelWhiteTexture = createTextureFromSource(
device, [255, 255, 255, 255]);
const rg16sint2x2 = [
1,2 3,4,
5,6, 7,8,
];
const rg16Texture2x2 = createTextureFromSource(
device, rg16sint2x2, { format: 'rg16sint' });
All data above can be a TypedArray
const singlePixelRedTexture = createTextureFromSource(
device, new Uint8Array[255, 0, 0, 255]);
import { numMipLevels, generateMipmap } from 'webgpu-utils';
const size = [8, 8, 1];
const texture = device.createTexture({
size,
mipLevelCount: numMipLevels(size);
format: 'rgba8unorm',
usage: GPUTextureUsage.TEXTURE_BINDING | GPUTextureUsage.RENDER_ATTACHMENT
});
... do whatever you do to fill out the mip level 0 ...
generateMipmap(device, texture);
import { numMipLevels, generateMipmap } from 'webgpu-utils';
const bi = wgh.createBuffersAndAttributesFromArrays(device, {
position: [1, 1, -1, 1, 1, 1, 1, -1, 1, 1, -1, -1, -1, 1, 1, -1, 1, -1, -1, -1, -1, -1, -1, 1, -1, 1, 1, 1, 1, 1, 1, 1, -1, -1, 1, -1, -1, -1, -1, 1, -1, -1, 1, -1, 1, -1, -1, 1, 1, 1, 1, -1, 1, 1, -1, -1, 1, 1, -1, 1, -1, 1, -1, 1, 1, -1, 1, -1, -1, -1, -1, -1],
normal: [1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1],
texcoord: [1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
indices: [0, 1, 2, 0, 2, 3, 4, 5, 6, 4, 6, 7, 8, 9, 10, 8, 10, 11, 12, 13, 14, 12, 14, 15, 16, 17, 18, 16, 18, 19, 20, 21, 22, 20, 22, 23],
});
const pipeline = device.createRenderPipeline({
layout: 'auto',
vertex: {
module,
entryPoint: 'myVSMain',
buffers: bi.bufferLayouts, // <---
},
...
});
// at render time
passEncoder.setVertexBuffer(0, bi.buffers[0]);
passEncoder.setIndexBuffer(bi.indexBuffer, bi.indexFormat);
passEncoder.drawIndexed(bi.numElements);
import {
makeShaderDataDefinitions,
makeBindGroupLayoutDescriptors,
} from 'webgpu-utils';
const code = `
@group(0) @binding(0) var<uniform> mat: mat4x4f;
struct MyVSOutput {
@builtin(position) position: vec4f,
@location(1) texcoord: vec2f,
};
@vertex
fn myVSMain(v: MyVSInput) -> MyVSOutput {
var vsOut: MyVSOutput;
vsOut.position = mat * v.position;
vsOut.texcoord = v.texcoord;
return vsOut;
}
@group(0) @binding(2) var diffuseSampler: sampler;
@group(0) @binding(3) var diffuseTexture: texture_2d<f32>;
@fragment
fn myFSMain(v: MyVSOutput) -> @location(0) vec4f {
return textureSample(diffuseTexture, diffuseSampler, v.texcoord);
}
`;
const module = device.createShaderModule({code});
const defs = wgh.makeShaderDataDefinitions(code);
const pipelineDesc = {
vertex: {
module,
entryPoint: 'myVSMain',
buffers: bufferLayouts,
},
fragment: {
module,
entryPoint: 'myFSMain',
targets: [
{format: presentationFormat},
],
},
};
const descriptors = wgh.makeBindGroupLayoutDescriptors(defs, pipelineDesc);
const group0Layout = device.createBindGroupLayout(descriptors[0]);
const layout = device.createPipelineLayout({
bindGroupLayouts: [group0Layout],
});
const pipeline = device.createRenderPipeline({
layout,
...pipelineDesc,
});
Example:
const code = `
@group(0) @binding(0) var<uniform> uni1: array<vec3f, 4>;
@group(0) @binding(1) var<uniform> uni2: array<array<vec3f, 3>, 4>;
`;
const defs = makeShaderDataDefinitions(code);
const uni1 = makeStructuredView(defs.uniforms.uni1);
const uni2 = makeStructuredView(defs.uniforms.uni2);
uni1.set([
1, 2, 3, 0, // uni1[0]
4, 5, 6, 0, // uni1[1]
//...
]);
uni2.set([
[
1, 2, 3, 0, // uni2[0][0],
4, 5, 6, 0, // uni2[0][1],
],
, // uni2[1]
[
7, 8, 9, 0, // uni2[2][0],
4, 5, 6, 0, // uni2[2][1],
],
]);
The reason it's this way is it's common to make large arrays of f32
, u32
,
vec2f
, vec3f
, vec4f
etc. We wouldn't want every element of an array to
have its own typedarray view.
You can configure this per type by calling setIntrinsicsToView
.
The configuration is global. Given th example above
const code = `
@group(0) @binding(0) var<uniform> uni1: array<vec3f, 4>;
@group(0) @binding(1) var<uniform> uni2: array<array<vec3f, 3>, 4>;
`;
const defs = makeShaderDataDefinitions(code);
setIntrinsicsToView(['vec3f']);
const uni1 = makeStructuredView(defs.uniforms.uni1);
uni1.set([
[1, 2, 3], // uni1[0]
[4, 5, 6], // uni1[1]
...
]);
Or to put it another way, in the default case, uni1.views is a Float32Array(16)
.
In the 2nd case it's an array of 4 Float32Array
each 3 elements big
const code = `
@group(0) @binding(0) var<uniform> uni1: array<vec2f, 4>;
`;
const defs = makeShaderDataDefinitions(code);
const uni1 = makeStructuredView(defs.uniforms.uni1);
uni1.set([
[1, 2], // uni1[0]
[3, 4], // uni1[1]
]);
Currently this requires the length of each subarray to match the length of
the intrinsic. The reason being, there is no type data used in uni1.set
so
there is nothing to tell it that it's a vec2f
. In this case, it just advances
where it's writing by the length of the source data sub arrays.
The reason is an unsized array's size is defined to WebGPU by its buffer binding
size. That information is provided at runtime so there's no way for webgpu-utils
to know the size. The solution is you pass in an ArrayBuffer
.
Example:
const code = `
@group(0) @binding(0) var<storage> buf1: array<vec3f>; // unsized array
`;
const defs = makeShaderDataDefinitions(code);
const buf1 = makeStructuredView(defs.storages.buf1, new ArrayBuffer(4 * 16));
// buf1.views will be a Float32Array representing 4 vec3fs
Note: If you have a complex array element type you can call
getSizeOfUnsizedArrayElement
to get its size. Example:
const code = `
struct Light {
intensity: f32,
direction: vec3f,
};
@group(0) @binding(7) var<storage> lights: array<Light>;
`;
const defs = makeShaderDataDefinitions(code);
const {size} = getSizeOfUnsizedArrayElement(defs.storages.lights);
const numLights = 4;
const buf1 = makeStructuredView(
defs.storages.lights, new ArrayBuffer(numLights * size));
Similarly if you are using an unsized array as the last member of a struct you might do this
const code = `
struct Kernel {
amount: f32,
entries: array<vec3f>,
};
@group(0) @binding(7) var<storage> conv: Kernel;
`;
const defs = makeShaderDataDefinitions(code);
const {size: elemSize} = getSizeOfUnsizedArrayElement(defs.storages.conv);
const numKernelEntries = 4;
const size = defs.storages.conv.size + numKernelEntries * elemSize;
const buf1 = makeStructuredView(
defs.storages.conv, new ArrayBuffer(size));
)
- include from the net
import { createTextureFromImage } from 'https://greggman.github.io/webgpu-utils/dist/1.x/webgpu-utils.module.js'
...
-
npm
npm install webgpu-utils
import { createTextureFromImage } from 'webgpu-utils';
...
git clone https://github.com/greggman/webgpu-utils.git
cd webgpu-utils
npm ci
npm start
This will run rollup in watch mode, building from typescript into
dist/1.x/webgpu-utils.js
and start a server
Now open http://localhost:8080/test/
to run tests.
Super thanks to Brendan Duncan for wgsl-reflect on which much of this is based.